The Paradigm Shift in Waste Valorization: An AI-Driven Next-Generation Recovery System

Amidst the continuous growth of global municipal solid waste (UN projected to reach 3.8 billion tons by 2050) and the inherent limitations of conventional management models, this paper investigates how technology-driven transformation, centered on artificial intelligence (AI), is precipitating a fundamental paradigm shift in waste resource recovery. The research posits that the core of this revolution lies in reconstructing a next-generation resource recovery system characterized by intelligent sensing, real-time interconnectivity, and dynamic self-adaptation. By integrating technologies such as high-precision visual recognition (accuracy >99%), intelligent robotic sorting, and digital twins, this system facilitates a paradigm leap in cognition and decision-making—from traditional "experience-driven" approaches to "data- and model-driven" methodologies. Empirical evidence demonstrates that this new paradigm not only multiplies sorting efficiency and stabilizes resource purity above 99%, but also through a "point-station-center" networked architecture and an intelligent management platform, establishes a closed-loop pathway for low-value recyclables from source separation to high-value utilization. This drives the transformation of the resource recycling industry toward a technology-intensive model. However, fully realizing this systemic change faces multifaceted challenges, including data quality, initial costs, policy coordination, and industrial chain integration. Future research should focus on the deep integration of AI technologies with circular economy principles, leveraging technological innovation to catalyze governance system innovation. This integration is pivotal for providing systemic solutions critical to achieving global "zero-waste city" and carbon neutrality goals.